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Disertacijoje nagrinėjama užstatytos aplinkos įtaka žmonių gyvenimo kokybei ir emocinei būsenai. Darbo tyrimų objektą sudaro užstatyta aplinka ir jame dalyvaujančios ir savo tikslus norinčios įgyvendinti suinteresuotos grupės. Disertacijos tikslas – sukurti užstatytos aplinkos daugiakriterės analizės rekomendacinį metodą (UADARM) ir sistemą (UADARS), leidžiančius suinteresuotoms grupėms (nekilnojamojo turto vystytojams, statybos bendrovėms, pastatus administruojančioms kompanijoms, savivaldybėms, projektuotojams, mokslo institucijoms ir t. t.) prisidėti kuriant ir valdant mus supančią aplinką. Darbe sprendžiami keli pagrindiniai uždaviniai: sukurti rekomendacinį metodą, identifikuoti rekomendacinės sistemos problemas ir įvertinti jų patikimumą. Remiantis parinktais metodais, pagrįsti duomenų analizės ir rekomendacinės sistemos naudingumas, duomenų analizės metodai ir rekomendacinė sistema ir atlikti empiriniai sukurtų sistemų patikrinimai. Disertaciją sudaro įvadas, trys skyriai, bendrosios išvados, naudotos literatūros ir autoriaus publikacijų disertacijos tema sąrašai ir 4 priedai. Pirmajame skyriuje apžvelgiami ankstesni tyrimai, susiję su užstatytos aplinkos įtaka žmonių emocinei būsenai, analizuojami matavimo metodai ir sistemos, galinčios tinkamai įvertinti emocinį lygį. Išvadose įvertinami ankstesni tyrimai ir apibendrinama, kas atlikta naujo šioje disertacijoje. Antrajame skyriuje aprašyta sukurta užstatytos aplinkos daugiakriterės analizės bei rekomendacinė sistema (UADARS), leidžianti matuoti, analizuoti ir atvaizduoti žmonių nuotaikas ir patogumo lygį užstatytoje aplinkoje. Ši sistema praktiškai išbandyta Vilniaus šviestų festivalio metu 2019 ir 2020 metais. Trečiajame skyriuje detaliai pateikta sukurta sumanių, adaptyvių pastatų valdymo sistema (SAPVS). Pasitelkus projekto naudingumo laipsnio ir investicinės vertės nustatymo, teikiant rekomendacijas (INVAR) (angl. Degree of Project Utility and Investment Value Assessments along with Recommendation Provisions) metodą, atlikta daugiakriterė SAPVS sistemos alternatyvų analizė ir skaičiavimai bei nustatytos geriausios alternatyvos, palengvinančios sprendimų priėmimą suinteresuotoms asmenų grupėms, ir suformuluotos išva-dos. Disertacijos tema paskelbti penki straipsniai. Du iš jų – „Clarivate Analytics Web of Science“ duomenų bazės leidiniuose. Publikuoti du pranešimai tarptautinėse konferencijose., Daktaro disertacija

Considerable research has been conducted globally showing how study results are substantially conditional to the interest and productivity of a learner in the studies and the emotions and stress the learner experiences. Scholars emphasize that learning should be pleasing, enticing, and emotionally positive leading to increased effectiveness of the studying. Tests were conducted regarding the effectiveness of the MSc Property management studies process among students. Development of the ARTSY Model involved five iterative phases over the course of the research. ARTSY Model, intelligent and physiological technologies that had helped as the foundation for creating the Affect-based, Multimodal, Video Tutoring System for a Neuromarketing (ARTSY) were applied for this research. The research motivation and one of the main purposes are to increase students learning productivity, interest, emotions and decrease stress levels. According to this research motivation, ARTSY was developed. Upon comparison with the most advanced, existing affective tutoring systems, two innovative elements are distinguishing ARTSY. First, automatic means to develop and select the most effective variants from thousands of textual and video learning material alternatives by considering learner interest, productivity and stress levels. Secondly, exams or tests are unnecessary for assessing student knowledge levels by employing the newly developed Calculating a Student’s Self-assessment Grade. ARTSY’s future betterments are expected to achieve comprehensive and dependable, real-time information, not only about student needs but also about existing opportunities. A consequent outcome could be greater flexibility in the study process for students. This paper composed of Introduction (Section 1), Research background (Section 2), ARTSY Model description (Section 3) and the Construction of ARTSY (Section 4). The conclusions and notes for future study provide the ending to this article in Section 5.

Multiple-criteria decision-making (MCDM) typically assumes that crowds make completely rational decisions. In MCDM, a crowd as a whole, or its individual members, generally make decisions free from any influence of valence, arousal, emotional state or environment. In contrast, various theories dealing with crowd psychology (Gustave Le Bon, Freudian, Deindividuation, Convergence, Emergent norm, Social identity) analyze, in one form or another, the emotions of the crowd. According to above theories, crowd is influenced by a range of behavioral factors, such as physical, social, psychological, culture, norms, and emotions. It can be argued that the emotional state, valence and arousal of crowds affect their decision making to a considerable degree and multiple criteria crowd behavior modeling must, therefore, consider this impact as well. In this light, the integration of crowd simulation and biometric methods, behavioral operations research and emotions in decision making has taken a prominent place as it leads to a better understanding of crowd emotions and crowd decision making. In this context, the authors developed the Affective Analytics of Demonstration Sites (ANDES) that added to this body of research in four ways. The crowd analysis and simulations conducted with ANDES used a neuro decision matrix. The matrix contains a detailed description of demonstration sites (public spaces) in question and the emotions, valence, arousal and physiological parameters of people present there. With ANDES’s Remote Sensor Network, emotional (emotions, valence, arousal) and physiological (average crowd facial temperature, crowd composition by gender and age group, etc.) parameters of people present at demonstration sites can be mapped. ANDES can assist experts in more effective implementations of public spaces planning and a participation process by attendees by collecting and examining various layers of data on the emotional and physiological parameters of visitors based on a visitors-centric public spaces planning approach. ANDES can determine the public space and real estate values.